Earth Science Analytics Awarded Subsea Upcoming Company of the Year
This year's winner of the Subsea Upcoming Company of the Year Award is pioneering the use of artificial intelligence and data analytics for petroleum geoscience.
The award is granted every year to a young company in the subsea industry. This year the award was granted to Earth Science Analytics based in iPark in Stavanger and Nyskapingsparken in Bergen. The award is granted by GCE Subsea, Sparebanken Vest and the Underwater Technology Foundation.
Earth Science Analytics are utilising the great potential of efficient analytical techniques that utilise all relevant data to further develop novel data analysis methods, leveraging artificial intelligence and machine learning technology. This, to deliver much more precise predictions, and to thus support more profitable investment decisions during hydrocarbon exploration and production.
Earth Science Analytics has extensive experience within geoscience, artificial intelligence, machine learning and algorithms, and use this to develop both technology and services for the oil and gas industry. The EarthNET software is based on artificial intelligence and provides geoscientists with an opportunity to work more efficiently, with greater precision and at a lower cost compared to traditional methods.
EarthNET can bridge the gap between large – multidimensional – datasets and data-driven decision making. Since moving in at Nyskapingsparken Incubator, the company has had a tremendous development far beyond the technical, which has resulted in a substantial customer portfolio, says Owe Hagesæther, CEO at GCE Subsea and head of the jury.
Finding and extracting hydrocarbons is difficult. Although large volumes of hydrocarbons remain to be found on the Norwegian Continental Shelf. The 187 exploration wells drilled over the last 5 years at a cost of 143 BNOK resulted in less than 10 commercial discoveries.
Underutilisation of data due to a lack of time, and insufficient calibration of geophysical methods are two of the causes behind the disappointing exploration results. The failure to utilise and integrate available data is partly a result of the inefficiency of traditional methods of data analysis. Large amounts of human expert labor, and financial resources were spent, to achieve the disappointing results of the past few years.
The as-yet untapped potential of efficient analytical techniques that utilises all relevant data encouraged us in Earth Science Analytics to further develop novel data analysis methods, leveraging artificial intelligence and machine Learning technology to improve exploration and production success.
Jury member and Regional Director at Sparebanken Vest, Margunn Aas Minne, is very excited about this year's winner. – Earth Science Analytics has demonstrated that they have a strong focus on the business model when it comes to the economy and the market. Their value proposition and business approach is very promising.
Sparebanken Vest has a long tradition of supporting regional businesses. Ass Minne says that the bank aims to contribute to the development of this type of high-tech business in Western Norway. – Subsea is a very important industry in our region, and it is a pleasure for us to cooperate with GCE Subsea in this respect, Aas Minne ends.
Earth Science Analytics is launching its cloud-based data analytics platform, EARTH NET, this month at the EAGE Conference and Exhibition in Copenhagen.
The Earth Science Analytics team argues that the incredibly rich subsurface dataset available through the Norwegian national data repository “Diskos”, can be used much more efficiently to deliver much more precise predictions, and to thus support more profitable investment decisions during hydrocarbon exploration and production. The EARTH NET platform enables this by integrating data management solutions with artificial intelligence and data analytics tools tailormade to handle petroleum geoscience data.
Behzad Alaei, Chief Data Officer, says that “Our approach to developing more efficient and precise analytical techniques is based on algorithms that can learn and make predictions directly from data. One key advantage of artificial intellignece in science is the technology’s ability to efficiently handle very large volumes of multidimensional data, thus saving time and cost and, therefore, allowing human resources to be deployed to other, perhaps more creative, tasks. Another advantage is machine learnings’s ability to detect complex patterns that are not readily visible to humans. We aim to solve the data under-utilisation problem by implementing artificial intelligence systems in petroleum geoscience. By doing so, we aim to provide more reliable and efficient methods for data analytics, and ultimately reduce the number of costly, unsuccessful wells. “
The oil and gas companies that, in the very near future, successfully apply the EARTH NET data analytics platform, and artificial intelligence-assisted petroleum geoscience technology will be able to efficiently use the large amounts of previously underutilised subsurface data. They will be able to handle multidimensional parameter sets in a purely data-driven way; which was not possible with the traditional technology and workflows. Artificial intelligence and data science will reduce human bias, which currently is pervasive in petroleum geosciences, and enable much more data-driven, and profitable investment-decisions in their search for oil and gas.
Although Earth Science Analytics started in Norway, leveraging the great national data repository “Diskos”, the company has already got a foothold in other countries such as the UK and Germany. Going forward the company is working on expanding across the Middle East and in South East Asia.
Earth Science Analytics have offices at iPark in Stavanger, and in Nyskapningsparken in Bergen. The founders took part in, and benefited greatly from the Subsea ACCEL Energy startup accelerator and the Nyskapingsparken incubator led by BTO. Earth Science Analytics has received commercialisation funding from Innovasjon Norge and a 7MNOK grant from the Research Council of Norway (Petromaks2) to further research artificial -applications for seismic data analysis.